This paper presents a Bayesian approach for bleed-through reduction in degraded document images based on a simple linear degradation model. A variation of ICM optimisation is used whereby samples are drawn for the bleed-through reduced images, whilst the remaining variables are estimated via the mode of their conditional probabilities. The proposed method is tested on various samples of scanned manuscript images with different degrees of degradation, and the results show some convincing removal of bleed-through.
{"title":"Degraded Document Bleed-Through Removal","authors":"Róisín Rowley-Brooke, A. Kokaram","doi":"10.1109/IMVIP.2011.21","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.21","url":null,"abstract":"This paper presents a Bayesian approach for bleed-through reduction in degraded document images based on a simple linear degradation model. A variation of ICM optimisation is used whereby samples are drawn for the bleed-through reduced images, whilst the remaining variables are estimated via the mode of their conditional probabilities. The proposed method is tested on various samples of scanned manuscript images with different degrees of degradation, and the results show some convincing removal of bleed-through.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124835765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In CT colonography, the first major step of colonic polyp detection is reliable segmentation of colon from CT data. In this paper, we propose a fast and accurate method for automatic colon segmentation from CT data using colon geometrical features. After removal of the lung and surrounding air voxels from CT data, labeling is performed to generate candidate regions for Colon segmentation. The centroid of the data, derived from the labeled objects is used to analyze the colon geometry. Other notable features that are used for colon segmentation are volume/length measure and end points. The proposed method was validated using a total of 99 patient datasets. Collapsed colon surface detection was 99.59% with an average of 1.59% extra colonic surface inclusion. The proposed technique takes 16.29 second to segment the colon from an abdomen CT dataset.
{"title":"A Fast and Accurate Method for Automatic Segmentation of Colons at CT Colonography Based on Colon Geometrical Features","authors":"T. A. Chowdhury, P. Whelan","doi":"10.1109/IMVIP.2011.25","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.25","url":null,"abstract":"In CT colonography, the first major step of colonic polyp detection is reliable segmentation of colon from CT data. In this paper, we propose a fast and accurate method for automatic colon segmentation from CT data using colon geometrical features. After removal of the lung and surrounding air voxels from CT data, labeling is performed to generate candidate regions for Colon segmentation. The centroid of the data, derived from the labeled objects is used to analyze the colon geometry. Other notable features that are used for colon segmentation are volume/length measure and end points. The proposed method was validated using a total of 99 patient datasets. Collapsed colon surface detection was 99.59% with an average of 1.59% extra colonic surface inclusion. The proposed technique takes 16.29 second to segment the colon from an abdomen CT dataset.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129977608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Murray, Michael Brogan, S. Haughey, S. McLoughlin, C. Deegan, C. Fitzgerald
This paper describes a short stereo baseline vision system capable of detecting retro reflective surfaces without the requirement of image correspondence.
本文描述了一种无需图像对应即可检测复古反射表面的短立体基线视觉系统。
{"title":"Short Stereo Baseline Retroreflector Detection Method","authors":"S. Murray, Michael Brogan, S. Haughey, S. McLoughlin, C. Deegan, C. Fitzgerald","doi":"10.1109/IMVIP.2011.32","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.32","url":null,"abstract":"This paper describes a short stereo baseline vision system capable of detecting retro reflective surfaces without the requirement of image correspondence.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115923732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An existing surface metrology algorithm, based on digital fringe projection, has been applied to measure specular discontinuous surfaces. Using in-house developed software, phase maps are measured by phase-stepping interferometry. Temporal Phase Unwrapping method is then used to perform unwrapping, leading to obtaining slope at every point on the reconstructed surface.
{"title":"An Investigation of Discontinious Specular Surfaces Using Non-contact In-Line Monitoring Techniques","authors":"Kiryl Kekukh, W. Doherty","doi":"10.1109/IMVIP.2011.35","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.35","url":null,"abstract":"An existing surface metrology algorithm, based on digital fringe projection, has been applied to measure specular discontinuous surfaces. Using in-house developed software, phase maps are measured by phase-stepping interferometry. Temporal Phase Unwrapping method is then used to perform unwrapping, leading to obtaining slope at every point on the reconstructed surface.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124055702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many silhouettes based features are proposed for gait recognition. But these methods suffer with covariate factors such as clothing and carrying objects. These covariate factors mostly attached with silhouettes and make gait recognition much difficult. Therefore we proposed a new silhouette based feature to analyse the influence of body parts and increase the recognition rate for individual identification.
{"title":"Analysis of Most Important Parts for Silhouette-Based Gait Recognition","authors":"Y. Pratheepan, J. Condell, G. Prasad","doi":"10.1109/IMVIP.2011.27","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.27","url":null,"abstract":"Many silhouettes based features are proposed for gait recognition. But these methods suffer with covariate factors such as clothing and carrying objects. These covariate factors mostly attached with silhouettes and make gait recognition much difficult. Therefore we proposed a new silhouette based feature to analyse the influence of body parts and increase the recognition rate for individual identification.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127107248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Victoria Ponz, A. Villanueva, Laura Sesma, M. Ariz, R. Cabeza
Low cost iris tracking is one of the most challenging research topics for the eye-tracking community. To this end, accurate detection of the iris centre in images captured by a web cam is a major goal. We propose a novel method for iris detection that is based on image topography using multi-resolution to detect the most stable "valley" over different resolutions, which is assumed to be the iris centre. Our algorithm was tested using the BioID database obtaining the best average behavior. Our algorithm functions in real time and does not require complex post processing stages.
{"title":"Topography-Based Detection of the Iris Centre Using Multiple-Resolution Images","authors":"Victoria Ponz, A. Villanueva, Laura Sesma, M. Ariz, R. Cabeza","doi":"10.1109/IMVIP.2011.15","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.15","url":null,"abstract":"Low cost iris tracking is one of the most challenging research topics for the eye-tracking community. To this end, accurate detection of the iris centre in images captured by a web cam is a major goal. We propose a novel method for iris detection that is based on image topography using multi-resolution to detect the most stable \"valley\" over different resolutions, which is assumed to be the iris centre. Our algorithm was tested using the BioID database obtaining the best average behavior. Our algorithm functions in real time and does not require complex post processing stages.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127455345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Richard Harrison, F. Bianconi, Richard Harvey, Wenjia Wang
Offshore wind farms are undergoing unprecedented development as EU member states focus on complying with 2020 renewable energy mandates. However, wind farm site placement requires great care, to avoid compromising protected habitats, such as Sabellaria spinulosa reefs. This paper presents an investigation into the potential of different feature generation methods for identifying sides can sonar image textures characteristic of Sabellaria spinulosa colonies. We propose an extensible test methodology and carry out a detailed comparison of several textural features. Our results show that Gabor filter bank features yield good (up to 89.4% overall) classification accuracies and often outperform other methods in identifying the Sabellaria spinulosa textural class. A Dual-Tree Complex Wavelet Transform, Ring filters and some statistical methods also produce encouraging results.
{"title":"A Texture Analysis Approach to Identifying Sabellaria Spinulosa Colonies in Sidescan Sonar Imagery","authors":"Richard Harrison, F. Bianconi, Richard Harvey, Wenjia Wang","doi":"10.1109/IMVIP.2011.19","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.19","url":null,"abstract":"Offshore wind farms are undergoing unprecedented development as EU member states focus on complying with 2020 renewable energy mandates. However, wind farm site placement requires great care, to avoid compromising protected habitats, such as Sabellaria spinulosa reefs. This paper presents an investigation into the potential of different feature generation methods for identifying sides can sonar image textures characteristic of Sabellaria spinulosa colonies. We propose an extensible test methodology and carry out a detailed comparison of several textural features. Our results show that Gabor filter bank features yield good (up to 89.4% overall) classification accuracies and often outperform other methods in identifying the Sabellaria spinulosa textural class. A Dual-Tree Complex Wavelet Transform, Ring filters and some statistical methods also produce encouraging results.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126938233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Intense current research requires quantitative analysis of cell behaviours in dense cell populations. The low contrast cellular image quality, diversity of cell shapes, frequent cell interactions, and complex cell motions all pose significant problems to the efficient and robust cell tracking in phase contrast cellular images. We have proposed an automated cell tracking system based on active contours for tracking cell deformation and movement. The pyramidal optic flow scheme is exploited for providing external motion force to guide active contour evolution, and thus helps to address the particular difficulty in tracking relatively fast moving cells in dense cell population. We have evaluated the proposed framework on one real cellular dataset and proved an 80.2% tracking accuracy.
{"title":"Optic Flow Providing External Force for Active Contours in Visually Tracking Dense Cell Population","authors":"Shan Yu, D. Molloy","doi":"10.1109/IMVIP.2011.24","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.24","url":null,"abstract":"Intense current research requires quantitative analysis of cell behaviours in dense cell populations. The low contrast cellular image quality, diversity of cell shapes, frequent cell interactions, and complex cell motions all pose significant problems to the efficient and robust cell tracking in phase contrast cellular images. We have proposed an automated cell tracking system based on active contours for tracking cell deformation and movement. The pyramidal optic flow scheme is exploited for providing external motion force to guide active contour evolution, and thus helps to address the particular difficulty in tracking relatively fast moving cells in dense cell population. We have evaluated the proposed framework on one real cellular dataset and proved an 80.2% tracking accuracy.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115869289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Gil, A. Bakermans, B. J. V. Nierop, G. Strijkers, H. V. Assen, K. Curran
The purpose of this paper is to register ex-vivo cardiac diffusion tensor images using affine transformations and the preservation of the principal direction reorientation strategy. We have successfully registered cardiac DTI and compared five different similarity measures: relative anisotropy difference, modulus difference, tensor difference, normalized tensor difference and principal direction difference. Results indicate that the principal direction difference is superior to the other similarity measures, followed by the normalized tensor difference and tensor difference. For cardiac DTI registration, measures sensitive to the full tensor perform better than scalar derived measures.
{"title":"Similarity Measures for Cardiac Diffusion Tensor Imaging Registration","authors":"C. Gil, A. Bakermans, B. J. V. Nierop, G. Strijkers, H. V. Assen, K. Curran","doi":"10.1109/IMVIP.2011.23","DOIUrl":"https://doi.org/10.1109/IMVIP.2011.23","url":null,"abstract":"The purpose of this paper is to register ex-vivo cardiac diffusion tensor images using affine transformations and the preservation of the principal direction reorientation strategy. We have successfully registered cardiac DTI and compared five different similarity measures: relative anisotropy difference, modulus difference, tensor difference, normalized tensor difference and principal direction difference. Results indicate that the principal direction difference is superior to the other similarity measures, followed by the normalized tensor difference and tensor difference. For cardiac DTI registration, measures sensitive to the full tensor perform better than scalar derived measures.","PeriodicalId":179414,"journal":{"name":"2011 Irish Machine Vision and Image Processing Conference","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132385467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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